'''simple docstring'''




from ....configuration_utils import PretrainedConfig
from ....utils import logging


__UpperCAmelCase					=logging.get_logger(__name__)

# TODO: upload to AWS
__UpperCAmelCase					={
    "yjernite/retribert-base-uncased": (
        "https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/config.json"
    ),
}




class        a__ (  UpperCAmelCase__					):
     lowerCamelCase    :	int				="retribert"






     def __init__(					self						:						int    ,							a						:						Tuple=3_05_22    ,							a						:						Tuple=7_68    ,							a						:						Optional[int]=8    ,							a						:						List[str]=12    ,							a						:						int=30_72    ,							a						:						List[Any]="gelu"    ,							a						:						Tuple=0.1    ,							a						:						Dict=0.1    ,							a						:						List[Any]=5_12    ,							a						:						List[str]=2    ,							a						:						Optional[int]=0.02    ,							a						:						List[Any]=1e-1_2    ,							a						:						List[str]=True    ,							a						:						Dict=1_28    ,							a						:						str=0    ,							**a						:						Tuple    ,							):





         """simple docstring"""



         super().__init__(pad_token_id=a    ,							**a       )

         __lowerCamelCase            =    vocab_size
         __lowerCamelCase            =    hidden_size
         __lowerCamelCase            =    num_hidden_layers
         __lowerCamelCase            =    num_attention_heads
         __lowerCamelCase            =    hidden_act
         __lowerCamelCase            =    intermediate_size
         __lowerCamelCase            =    hidden_dropout_prob
         __lowerCamelCase            =    attention_probs_dropout_prob
         __lowerCamelCase            =    max_position_embeddings
         __lowerCamelCase            =    type_vocab_size
         __lowerCamelCase            =    initializer_range
         __lowerCamelCase            =    layer_norm_eps
         __lowerCamelCase            =    share_encoders
         __lowerCamelCase            =    projection_dim

'''simple docstring'''




import timeit

import numpy as np

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD






def __lowerCAmelCase					(				UpperCamelCase__							)      ->       List[str]:
    def wrapper(*UpperCamelCase__							,    **UpperCamelCase__							):
        __lowerCamelCase            =    timeit.default_timer()
        __lowerCamelCase            =    func(*UpperCamelCase__							,    **UpperCamelCase__							)
        __lowerCamelCase            =    timeit.default_timer() - starttime
        return delta

    __lowerCamelCase            =    func.__name__

    return wrapper






def __lowerCAmelCase					(				UpperCamelCase__							,    UpperCamelCase__=1_00							,    UpperCamelCase__=None							)      ->       Dict:
    __lowerCamelCase            =    []
    __lowerCamelCase            =    seq_shapes or {}
    for i in range(UpperCamelCase__							):
        __lowerCamelCase            =    {}
        for col_id, (k, v) in enumerate(features.items()							):
            if isinstance(UpperCamelCase__							,    _ArrayXD							):
                __lowerCamelCase            =    np.random.rand(*v.shape							).astype(v.dtype							)
            elif isinstance(UpperCamelCase__							,    datasets.Value							):
                if v.dtype == "string":
                    __lowerCamelCase            =    '''The small grey turtle was surprisingly fast when challenged.'''
                else:
                    __lowerCamelCase            =    np.random.randint(10							,    size=1							).astype(v.dtype							).item()
            elif isinstance(UpperCamelCase__							,    datasets.Sequence							):
                while isinstance(UpperCamelCase__							,    datasets.Sequence							):
                    __lowerCamelCase            =    v.feature
                __lowerCamelCase            =    seq_shapes[k]
                __lowerCamelCase            =    np.random.rand(*UpperCamelCase__							).astype(v.dtype							)
            __lowerCamelCase            =    data

        dummy_data.append((i, example)							)

    return dummy_data






def __lowerCAmelCase					(				UpperCamelCase__							,    UpperCamelCase__							,    UpperCamelCase__=1_00							,    UpperCamelCase__=None							)      ->       Dict:
    __lowerCamelCase            =    generate_examples(UpperCamelCase__							,    num_examples=UpperCamelCase__							,    seq_shapes=UpperCamelCase__							)

    with ArrowWriter(features=UpperCamelCase__							,    path=UpperCamelCase__							) as writer:
        for key, record in dummy_data:
            __lowerCamelCase            =    features.encode_example(UpperCamelCase__							)
            writer.write(UpperCamelCase__							)

        __lowerCamelCase      ,    __lowerCamelCase            =    writer.finalize()

    if not num_final_examples == num_examples:
        raise ValueError(
            f"""Error writing the dataset, wrote {num_final_examples} examples but should have written {num_examples}."""							)

    __lowerCamelCase            =    datasets.Dataset.from_file(filename=UpperCamelCase__							,    info=datasets.DatasetInfo(features=UpperCamelCase__							)							)

    return dataset
